Personalization in e-learning: the adaptive system vs. the intelligent agent approaches

Nowadays it is essential to obtain personalization in e-learning, to provide help to students' activities in this environment. There are two main research directions that aim at providing personalization in e-learning: adaptive educational systems and intelligent tutors (agents). This paper presents the adaptability approach designed for the AdaptWeb system and the eTeacher agent, describing design and implementation issues, and discussing results obtained from students' evaluation in these real applications. Then, this paper presents a comparison about them.

[1]  Jakob Nielsen,et al.  Designing Web Usability: The Practice of Simplicity , 1999 .

[2]  Peter Brusilovsky,et al.  ELM-ART: An Intelligent Tutoring System on World Wide Web , 1996, Intelligent Tutoring Systems.

[3]  Antonija Mitrovic,et al.  KERMIT: A Constraint-Based Tutor for Database Modeling , 2002, Intelligent Tutoring Systems.

[4]  Christoph Peylo,et al.  W2 - Adaptive and Intelligent Web-Based Education Systems , 2003, Intelligent Tutoring Systems.

[5]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[6]  Martha W. Evens,et al.  CIRCSIM-Tutor: An Intelligent Tutoring System Using Natural Language Dialogue , 1997, ANLP.

[7]  José Palazzo Moreira de Oliveira,et al.  AdaptWeb: an Adaptive Web-based Courseware , 2003 .

[8]  Ramon Fabregat,et al.  UN SISTEMA DE TUTORÍA INTELIGENTE ADAPTATIVO CONSIDERANDO ESTILOS DE APRENDIZAJE , 2012 .

[9]  Wolfgang Nejdl,et al.  Adaptation in Open Corpus Hypermedia , 2001 .

[10]  Analía Amandi,et al.  eTeacher: Providing personalized assistance to e-learning students , 2008, Comput. Educ..

[11]  Diane J. Litman,et al.  Responding to Student Uncertainty During Computer Tutoring: An Experimental Evaluation , 2008, Intelligent Tutoring Systems.

[12]  Ben Shneiderman,et al.  Direct manipulation vs. interface agents , 1997, INTR.

[13]  Peter Brusilovsky,et al.  Adaptive Hypermedia , 2001, User Modeling and User-Adapted Interaction.

[14]  Analía Amandi,et al.  Evaluating Bayesian networks' precision for detecting students' learning styles , 2007, Comput. Educ..

[15]  Pattie Maes,et al.  Agents that reduce work and information overload , 1994, CACM.

[16]  Ann Blandford,et al.  MLTutor: An Application of Machine Learning Algorithms for an Adaptive Web-based Information System , 2003, Int. J. Artif. Intell. Educ..

[17]  Antonija Mitrovic,et al.  An Intelligent SQL Tutor on the Web , 2003, Int. J. Artif. Intell. Educ..

[18]  Analía Amandi,et al.  User - interface agent interaction: personalization issues , 2004, Int. J. Hum. Comput. Stud..